The focus was on the value of AI in modelling behaviours and changes in behaviour over time, to assess if a player is developing a problem. Detecting signs of problem gambling at an early stage greatly improves the ability to successfully prevent a continued destructive gaming pattern.

Past research in responsible gambling has identified several critical factors such as the amount a player stakes, the time he/she plays for and how they deposit money. However, everyone is different, and so there is no universal solution to detecting the problem.

Will Mace, Head of Kindred Futures, said: “This was a fascinating discussion, bringing together experts from several different fields. The outcome was very encouraging – we agreed there was significant potential for an AI capability to bring together and analyse many data sources to give a much-improved ability to detect signs of a developing problem. We also agreed there was real value in doing this – both socially and commercially.”

AI and machine learning will potentially serve as a complement to Kindred Group’s proprietary system PS-EDS (Player Safety Early Detection System), as an addition to the set of tools and systems used by a Kindred team which hopes to further limit the small number of customers who see gambling as a challenge rather than a form of entertainment.